Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "169"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 169 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 27 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 25 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 169, Node N15:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459842 digital_ok 0.00% 0.00% 0.00% 0.00% 0.00% 0.00% 1.875249 1.142335 0.000934 -0.726556 -1.830747 -2.284595 -2.154359 -1.817329 0.7583 0.6629 0.2719 2.093547 1.916276
2459841 digital_ok 100.00% 0.00% 0.00% 0.00% - - 39.060144 41.488719 115.513172 117.260630 78.927648 111.066121 2.008640 5.533908 0.7540 0.7316 0.3636 nan nan
2459839 digital_ok 100.00% - - - - - 0.495186 -0.324138 -0.144431 -0.503128 2.287433 2.540357 17.097828 7.089500 nan nan nan nan nan
2459838 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 7.459649 5.644173 22.279800 21.104904 12.243858 19.076278 -2.127381 -1.629027 0.7240 0.6814 0.4337 0.000000 0.000000
2459836 digital_ok - 0.00% 0.00% 0.00% - - nan nan nan nan nan nan nan nan 0.7252 0.6600 0.4001 nan nan
2459835 digital_ok 100.00% 0.00% 0.00% 0.00% - - 4.869021 5.205427 12.211016 12.066701 8.549322 8.854112 -7.039172 -5.812032 0.8066 0.6006 0.4873 nan nan
2459833 digital_ok 100.00% 0.00% 0.00% 0.00% - - 15.164483 15.775072 53.428817 53.432235 73.270188 69.319943 -3.817450 -6.354631 0.8151 0.5670 0.4992 nan nan
2459832 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 14.895902 15.310444 18.004373 17.092881 10.535737 9.023629 -0.517313 -0.442255 0.7976 0.4929 0.6038 4.329639 3.188077
2459831 digital_ok 100.00% 100.00% 100.00% 0.00% - - 0.147668 -0.495203 -0.195766 -0.390202 2.922715 1.142897 11.660297 4.600756 0.0282 0.0276 0.0015 nan nan
2459830 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 16.145346 16.247001 23.820336 22.706755 30.917698 26.912224 -3.971158 -4.514501 0.7934 0.4927 0.5886 5.106894 3.410092
2459829 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459828 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 14.222338 14.324788 18.092255 17.296528 29.429517 25.848133 -1.767780 -3.128471 0.7853 0.5044 0.5573 5.438919 3.054721
2459827 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 11.327277 9.943659 29.995046 28.672496 18.681960 18.882120 -1.643079 5.068762 0.7488 0.6505 0.4378 9.790375 6.347387
2459826 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 14.138238 13.944232 24.287056 23.428817 39.010082 34.747988 0.695365 2.293756 0.7797 0.5314 0.5326 5.186373 3.225279
2459825 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 15.252810 14.597722 18.691877 17.871482 26.075564 23.949916 4.352035 4.144401 0.7721 0.5189 0.5443 0.000000 0.000000
2459824 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 9.001423 6.035744 26.322825 25.080895 11.570551 16.042175 7.589872 7.718288 0.6854 0.7038 0.4084 0.000000 0.000000
2459823 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 18.556653 17.424104 20.513580 19.756664 26.962562 27.126795 14.120724 14.073687 0.7277 0.5951 0.5079 0.000000 0.000000
2459822 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 16.959956 16.158182 22.694879 21.784487 24.973400 23.077993 -0.251870 0.117565 0.7680 0.5368 0.5351 0.000000 0.000000
2459821 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 18.422432 17.965949 22.290156 21.722275 22.511530 21.719395 -0.609682 0.024899 0.7490 0.5325 0.5323 4.115205 3.921890
2459820 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 13.309042 11.825461 27.175495 25.951389 52.368342 50.907053 -3.803842 -3.714368 0.7475 0.6428 0.4479 0.000000 0.000000
2459817 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 18.406271 17.677240 18.538616 17.929828 29.386027 28.513965 2.935570 4.483621 0.7521 0.5685 0.5217 0.964177 0.965191
2459816 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 12.810117 12.577292 27.154867 25.657806 38.310486 35.861654 -4.574350 -4.838867 0.8253 0.5440 0.6166 3.870969 2.766173
2459815 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 169: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Shape 1.875249 1.875249 1.142335 0.000934 -0.726556 -1.830747 -2.284595 -2.154359 -1.817329

Antenna 169: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok nn Power 117.260630 39.060144 41.488719 115.513172 117.260630 78.927648 111.066121 2.008640 5.533908

Antenna 169: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Discontinuties 17.097828 -0.324138 0.495186 -0.503128 -0.144431 2.540357 2.287433 7.089500 17.097828

Antenna 169: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Power 22.279800 5.644173 7.459649 21.104904 22.279800 19.076278 12.243858 -1.629027 -2.127381

Antenna 169: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Power 12.211016 5.205427 4.869021 12.066701 12.211016 8.854112 8.549322 -5.812032 -7.039172

Antenna 169: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 73.270188 15.775072 15.164483 53.432235 53.428817 69.319943 73.270188 -6.354631 -3.817450

Antenna 169: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Power 18.004373 14.895902 15.310444 18.004373 17.092881 10.535737 9.023629 -0.517313 -0.442255

Antenna 169: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Discontinuties 11.660297 0.147668 -0.495203 -0.195766 -0.390202 2.922715 1.142897 11.660297 4.600756

Antenna 169: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 30.917698 16.145346 16.247001 23.820336 22.706755 30.917698 26.912224 -3.971158 -4.514501

Antenna 169: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok nn Shape nan nan nan inf inf nan nan nan nan

Antenna 169: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 29.429517 14.324788 14.222338 17.296528 18.092255 25.848133 29.429517 -3.128471 -1.767780

Antenna 169: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Power 29.995046 11.327277 9.943659 29.995046 28.672496 18.681960 18.882120 -1.643079 5.068762

Antenna 169: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 39.010082 13.944232 14.138238 23.428817 24.287056 34.747988 39.010082 2.293756 0.695365

Antenna 169: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 26.075564 14.597722 15.252810 17.871482 18.691877 23.949916 26.075564 4.144401 4.352035

Antenna 169: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Power 26.322825 9.001423 6.035744 26.322825 25.080895 11.570551 16.042175 7.589872 7.718288

Antenna 169: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok nn Temporal Variability 27.126795 17.424104 18.556653 19.756664 20.513580 27.126795 26.962562 14.073687 14.120724

Antenna 169: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 24.973400 16.959956 16.158182 22.694879 21.784487 24.973400 23.077993 -0.251870 0.117565

Antenna 169: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 22.511530 17.965949 18.422432 21.722275 22.290156 21.719395 22.511530 0.024899 -0.609682

Antenna 169: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 52.368342 13.309042 11.825461 27.175495 25.951389 52.368342 50.907053 -3.803842 -3.714368

Antenna 169: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 29.386027 18.406271 17.677240 18.538616 17.929828 29.386027 28.513965 2.935570 4.483621

Antenna 169: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok ee Temporal Variability 38.310486 12.577292 12.810117 25.657806 27.154867 35.861654 38.310486 -4.838867 -4.574350

Antenna 169: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok nn Shape nan nan nan inf inf nan nan nan nan

Antenna 169: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 169: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
169 N15 digital_ok nn Shape nan nan nan inf inf nan nan nan nan
In [ ]: